DHA Service Access and Coverage

Analysis of population coverage and accessibility of Department of Home Affairs offices across South Africa

1 Overview

Birth and death registration may be incomplete due to the inaccessibility of Home Affairs offices where registration occurs. A potential barrier to registration may be the distance needed to travel. We aim to determine the proportion of the population within reasonable distances of Home Affairs offices.

2 Methodology

2.1 Data Sources

• Shape files: District boundaries from Stats SA, standardised using the {NMCleaner} package
• Population estimates: Stats SA mid-year population estimates (2025), at district level
• Office locations: DHA office coordinates from existing dataset (excludes hospital satellite offices)

2.2 Analytical Approach

We explored three approaches to estimate population coverage:

1. Office-to-office distance: Measured median half-distance between nearest office pairs. This underestimated coverage in rural areas.

2. Uniform grid distribution: Created 1km grid and distributed population uniformly within districts. Ignored population clustering.

3. Inverse power model (selected): Assumed population clusters around offices with distance decay.

2.3 Population Density Models

Inverse Power Model: \[ w_i = \frac{1}{(d_i + 1)^{\alpha}} \]

where \(d_i\) is the distance (km) from grid point \(i\) to the nearest office, and \(\alpha = 1.5\) is the decay parameter.

Population Allocation:

Weights are normalised within each district: \[ \hat{w}_i = \frac{w_i}{\sum_{j \in d} w_j} \]

The population at each grid point is: \[ P_i = P_d \cdot \hat{w}_i \]

where \(P_d\) is the total population of district \(d\).

2.4 Limitations

• Population is modelled, not observed at sub-district level
• Distances are straight-line, not road-network or travel-time
• Office capacity and service quality are not accounted for
• Satellite offices (e.g., in hospitals) are not included

3 National Overview Maps

3.1 Population Distribution by District

3.2 Number of DHA Offices by District

3.3 Modelled Population Distribution

4 Coverage Summary

Table 1

District	Total Population	Population within 10 km	% Population within 10 km	Population within 20 km	% Population within 20 km	Median Distance to Nearest DHA Office (km)
Alfred Nzo	935,303.24	455,653.79	48.71723	743,055.57	79.44542	10.402110
Amajuba	610,840.87	248,304.97	40.64970	412,243.37	67.48785	6.721991
Amathole	792,612.28	384,503.90	48.51097	624,102.29	78.73992	13.710934
Bojanala Platinum	1,985,081.47	973,231.05	49.02726	1,498,577.12	75.49197	6.631565
Buffalo City	0.00	0.00		0.00		6.645311
Cape Winelands	1,014,431.61	393,345.32	38.77495	660,490.34	65.10940	22.244051
Capricorn	1,412,657.09	704,095.36	49.84192	1,090,471.68	77.19295	6.588786
Central Karoo	77,156.77	19,337.85	25.06306	33,406.26	43.29660	61.232752
Chris Hani	717,288.80	284,460.44	39.65773	477,556.61	66.57801	18.530152
City of Cape Town	5,030,496.59	4,099,371.70	81.49040	4,680,808.63	93.04864	5.701034
City of Johannesburg	5,900,321.36	5,628,983.35	95.40130	5,892,801.12	99.87255	4.655293
City of Tshwane	4,038,060.52	2,807,261.12	69.52004	3,797,729.06	94.04834	6.261707
Dr Kenneth Kaunda	807,057.02	306,765.87	38.01043	534,494.42	66.22759	26.442373
Dr Ruth Segomotsi Mompati	474,901.42	126,706.75	26.68064	226,657.34	47.72724	37.381759
Ehlanzeni	1,928,692.28	949,462.10	49.22828	1,514,775.37	78.53899	14.563862
Ekurhuleni	4,059,057.15	3,606,628.50	88.85385	4,026,309.04	99.19321	4.287919
Fezile Dabi	536,755.09	210,021.56	39.12801	354,981.92	66.13480	25.841309
Frances Baard	438,828.63	252,121.61	57.45332	344,875.36	78.58999	6.517864
Garden Route	673,192.44	231,968.78	34.45802	359,566.57	53.41215	26.215135
Gert Sibande	1,367,512.57	499,243.04	36.50738	865,389.43	63.28201	23.991729
Harry Gwala	507,708.07	244,651.59	48.18745	393,554.66	77.51593	14.683459
Joe Gqabi	354,930.59	120,698.07	34.00611	201,178.45	56.68107	26.070329
John Taolo Gaetsewe	296,434.12	60,903.61	20.54541	105,421.63	35.56326	58.748156
King Cetshwayo	992,551.26	584,674.80	58.90626	878,507.60	88.51005	11.117175
Lejweleputswa	698,356.31	237,432.69	33.99879	415,209.16	59.45520	21.777022
Mangaung	857,972.98	368,652.30	42.96782	569,401.61	66.36591	7.357610
Mopani	1,266,833.75	637,248.98	50.30249	965,505.48	76.21406	11.449517
Namakwa	129,514.62	18,622.61	14.37877	32,227.66	24.88342	101.611559
Nelson Mandela Bay	1,263,632.35	913,989.64	72.33034	1,177,353.23	93.17213	5.560911
Ngaka Modiri Molema	916,906.71	356,376.61	38.86727	585,529.12	63.85918	11.025078
Nkangala	1,779,928.23	915,034.71	51.40852	1,379,989.56	77.53063	14.948017
O.R. Tambo	1,623,984.18	901,159.23	55.49064	1,383,466.86	85.18968	11.402136
Overberg	329,835.08	129,158.89	39.15863	214,444.59	65.01570	29.774281
Pixley ka Seme	219,155.39	44,534.82	20.32111	78,796.01	35.95440	60.644279
Sarah Baartman	527,417.58	137,390.39	26.04964	236,924.35	44.92159	36.350580
Sedibeng	1,061,184.78	698,345.41	65.80809	956,981.76	90.18050	5.241618
Sekhukhune	1,333,431.61	623,523.74	46.76083	1,030,150.20	77.25557	13.957115
Thabo Mofutsanyana	810,097.04	281,905.92	34.79903	474,806.88	58.61111	21.412738
Ugu	831,709.41	410,976.35	49.41345	648,175.00	77.93287	15.690580
Umzinyathi	607,975.36	279,572.67	45.98421	481,574.42	79.20953	20.312587
Vhembe	1,527,097.27	814,783.91	53.35508	1,210,957.63	79.29800	11.353646
Waterberg	826,172.40	270,753.13	32.77199	469,022.86	56.77058	20.385642
West Coast	502,575.67	158,658.18	31.56901	266,240.56	52.97522	53.950602
West Rand	1,046,309.52	595,362.01	56.90114	881,712.99	84.26885	6.530380
Xhariep	136,652.09	32,346.18	23.67046	58,520.08	42.82414	32.967104
ZF Mgcawu	295,250.15	65,364.51	22.13869	109,046.04	36.93344	49.658992
Zululand	901,274.60	416,978.23	46.26539	696,858.99	77.31928	14.419205
eThekwini	4,374,202.14	3,566,220.60	81.52848	4,314,338.52	98.63144	4.116189
iLembe	742,038.00	487,512.25	65.69910	715,374.15	96.40667	14.468760
uMgungundlovu	1,220,477.11	558,332.70	45.74708	974,950.39	79.88273	18.124755
uMkhanyakude	711,366.32	369,937.77	52.00383	571,470.34	80.33419	20.035972
uThukela	732,104.09	233,310.61	31.86850	401,013.65	54.77550	28.928896
Total	62,225,325.98	37,715,880.17	60.61178	51,016,995.93	81.98751	13.856925

5 Interactive Map

Explore DHA office locations with coverage buffers (10km, 20km, 50km).

6 Key Findings

ImportantSummary Statistics

• XX% of the population lives within 10km of a DHA office
• XX% of the population lives within 20km of a DHA office
• Rural districts show significantly lower coverage

7 Recommendations

1. Request enumeration area data: Census data at smaller geographic units would improve population distribution estimates
2. Include satellite offices: Hospital-based registration points should be mapped
3. Road network analysis: Travel time may be more relevant than straight-line distance